{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c21a43f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "70e9d2ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['font.sans-serif']=['SimHei']  # 用来正常显示中文标签 \n",
    "plt.rcParams['axes.unicode_minus']=False  # 用来正常显示负号"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6a160f03",
   "metadata": {},
   "outputs": [],
   "source": [
    "# df_train = pd.read_csv('训练日志-训练集.csv')\n",
    "# df_test = pd.read_csv('训练日志-测试集.csv')\n",
    "df_train = pd.read_csv(r'checkpoint_1\\训练日志-训练集.csv')\n",
    "df_test = pd.read_csv(r'checkpoint_1\\训练日志-测试集.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0b9df0a6",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch</th>\n",
       "      <th>batch</th>\n",
       "      <th>train_loss</th>\n",
       "      <th>train_accuracy</th>\n",
       "      <th>train_precision</th>\n",
       "      <th>train_recall</th>\n",
       "      <th>train_f1-score</th>\n",
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       "      <td>4.496822</td>\n",
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       "      <td>0.008130</td>\n",
       "      <td>0.012195</td>\n",
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       "      <td>0.404762</td>\n",
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       "    <tr>\n",
       "      <th>22398</th>\n",
       "      <td>50</td>\n",
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       "      <td>0.843750</td>\n",
       "      <td>0.774194</td>\n",
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       "<p>22401 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       epoch  batch  train_loss  train_accuracy  train_precision  \\\n",
       "0          0      0    4.393763        0.000000         0.000000   \n",
       "1          1      1    4.566897        0.000000         0.000000   \n",
       "2          1      2    4.641534        0.000000         0.000000   \n",
       "3          1      3    4.544966        0.000000         0.000000   \n",
       "4          1      4    4.496822        0.031250         0.008130   \n",
       "...      ...    ...         ...             ...              ...   \n",
       "22396     50  22396    0.910816        0.718750         0.630208   \n",
       "22397     50  22397    1.134321        0.593750         0.457143   \n",
       "22398     50  22398    0.751424        0.843750         0.774194   \n",
       "22399     50  22399    0.894228        0.812500         0.645161   \n",
       "22400     50  22400    0.874889        0.888889         0.800000   \n",
       "\n",
       "       train_recall  train_f1-score  \n",
       "0          0.000000        0.000000  \n",
       "1          0.000000        0.000000  \n",
       "2          0.000000        0.000000  \n",
       "3          0.000000        0.000000  \n",
       "4          0.012195        0.009756  \n",
       "...             ...             ...  \n",
       "22396      0.593750        0.597917  \n",
       "22397      0.404762        0.422857  \n",
       "22398      0.741935        0.752688  \n",
       "22399      0.629032        0.634409  \n",
       "22400      0.800000        0.800000  \n",
       "\n",
       "[22401 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "af2f427f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epoch</th>\n",
       "      <th>test_loss</th>\n",
       "      <th>test_accuracy</th>\n",
       "      <th>test_precision</th>\n",
       "      <th>test_recall</th>\n",
       "      <th>test_f1-score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.574569</td>\n",
       "      <td>0.010147</td>\n",
       "      <td>0.007555</td>\n",
       "      <td>0.010026</td>\n",
       "      <td>0.005400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.640199</td>\n",
       "      <td>0.587538</td>\n",
       "      <td>0.609600</td>\n",
       "      <td>0.562140</td>\n",
       "      <td>0.547563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.113720</td>\n",
       "      <td>0.702730</td>\n",
       "      <td>0.718815</td>\n",
       "      <td>0.679856</td>\n",
       "      <td>0.673580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.894771</td>\n",
       "      <td>0.753895</td>\n",
       "      <td>0.749061</td>\n",
       "      <td>0.737337</td>\n",
       "      <td>0.731096</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.0</td>\n",
       "      <td>0.853364</td>\n",
       "      <td>0.757182</td>\n",
       "      <td>0.771304</td>\n",
       "      <td>0.740462</td>\n",
       "      <td>0.739676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>0.735964</td>\n",
       "      <td>0.790196</td>\n",
       "      <td>0.801927</td>\n",
       "      <td>0.778574</td>\n",
       "      <td>0.776723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.614825</td>\n",
       "      <td>0.831785</td>\n",
       "      <td>0.830787</td>\n",
       "      <td>0.820846</td>\n",
       "      <td>0.818731</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.583118</td>\n",
       "      <td>0.837931</td>\n",
       "      <td>0.838710</td>\n",
       "      <td>0.827599</td>\n",
       "      <td>0.827473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.584160</td>\n",
       "      <td>0.834929</td>\n",
       "      <td>0.842948</td>\n",
       "      <td>0.824302</td>\n",
       "      <td>0.824956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.539541</td>\n",
       "      <td>0.846077</td>\n",
       "      <td>0.850743</td>\n",
       "      <td>0.838852</td>\n",
       "      <td>0.839070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10.0</td>\n",
       "      <td>0.519353</td>\n",
       "      <td>0.853080</td>\n",
       "      <td>0.854708</td>\n",
       "      <td>0.843748</td>\n",
       "      <td>0.844910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.467613</td>\n",
       "      <td>0.868801</td>\n",
       "      <td>0.867242</td>\n",
       "      <td>0.860473</td>\n",
       "      <td>0.860667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12.0</td>\n",
       "      <td>0.473727</td>\n",
       "      <td>0.863799</td>\n",
       "      <td>0.867511</td>\n",
       "      <td>0.856654</td>\n",
       "      <td>0.857112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.445921</td>\n",
       "      <td>0.875089</td>\n",
       "      <td>0.878064</td>\n",
       "      <td>0.867848</td>\n",
       "      <td>0.869226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14.0</td>\n",
       "      <td>0.442008</td>\n",
       "      <td>0.873374</td>\n",
       "      <td>0.875287</td>\n",
       "      <td>0.865314</td>\n",
       "      <td>0.866243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15.0</td>\n",
       "      <td>0.431930</td>\n",
       "      <td>0.875804</td>\n",
       "      <td>0.877096</td>\n",
       "      <td>0.868570</td>\n",
       "      <td>0.868688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16.0</td>\n",
       "      <td>0.432575</td>\n",
       "      <td>0.878091</td>\n",
       "      <td>0.878309</td>\n",
       "      <td>0.870731</td>\n",
       "      <td>0.870972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17.0</td>\n",
       "      <td>0.414128</td>\n",
       "      <td>0.879377</td>\n",
       "      <td>0.879558</td>\n",
       "      <td>0.871829</td>\n",
       "      <td>0.873091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18.0</td>\n",
       "      <td>0.410965</td>\n",
       "      <td>0.882807</td>\n",
       "      <td>0.883459</td>\n",
       "      <td>0.875738</td>\n",
       "      <td>0.876549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19.0</td>\n",
       "      <td>0.409568</td>\n",
       "      <td>0.883950</td>\n",
       "      <td>0.883950</td>\n",
       "      <td>0.876857</td>\n",
       "      <td>0.877309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20.0</td>\n",
       "      <td>0.403658</td>\n",
       "      <td>0.885665</td>\n",
       "      <td>0.886299</td>\n",
       "      <td>0.879155</td>\n",
       "      <td>0.879998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21.0</td>\n",
       "      <td>0.401694</td>\n",
       "      <td>0.888952</td>\n",
       "      <td>0.887909</td>\n",
       "      <td>0.881970</td>\n",
       "      <td>0.882710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22.0</td>\n",
       "      <td>0.407843</td>\n",
       "      <td>0.885665</td>\n",
       "      <td>0.885989</td>\n",
       "      <td>0.879738</td>\n",
       "      <td>0.880079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23.0</td>\n",
       "      <td>0.406923</td>\n",
       "      <td>0.883807</td>\n",
       "      <td>0.883532</td>\n",
       "      <td>0.876419</td>\n",
       "      <td>0.876910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24.0</td>\n",
       "      <td>0.395577</td>\n",
       "      <td>0.887809</td>\n",
       "      <td>0.889552</td>\n",
       "      <td>0.882043</td>\n",
       "      <td>0.882780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25.0</td>\n",
       "      <td>0.389501</td>\n",
       "      <td>0.889381</td>\n",
       "      <td>0.889916</td>\n",
       "      <td>0.883888</td>\n",
       "      <td>0.884429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26.0</td>\n",
       "      <td>0.387741</td>\n",
       "      <td>0.889667</td>\n",
       "      <td>0.889984</td>\n",
       "      <td>0.883749</td>\n",
       "      <td>0.884701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27.0</td>\n",
       "      <td>0.391301</td>\n",
       "      <td>0.890810</td>\n",
       "      <td>0.891261</td>\n",
       "      <td>0.884622</td>\n",
       "      <td>0.885266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28.0</td>\n",
       "      <td>0.383794</td>\n",
       "      <td>0.890382</td>\n",
       "      <td>0.892840</td>\n",
       "      <td>0.883700</td>\n",
       "      <td>0.884852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29.0</td>\n",
       "      <td>0.383601</td>\n",
       "      <td>0.890810</td>\n",
       "      <td>0.890535</td>\n",
       "      <td>0.884430</td>\n",
       "      <td>0.884803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>30.0</td>\n",
       "      <td>0.389712</td>\n",
       "      <td>0.887952</td>\n",
       "      <td>0.887850</td>\n",
       "      <td>0.882333</td>\n",
       "      <td>0.882741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>31.0</td>\n",
       "      <td>0.380165</td>\n",
       "      <td>0.891382</td>\n",
       "      <td>0.891478</td>\n",
       "      <td>0.885527</td>\n",
       "      <td>0.885894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>32.0</td>\n",
       "      <td>0.382717</td>\n",
       "      <td>0.893383</td>\n",
       "      <td>0.893900</td>\n",
       "      <td>0.887149</td>\n",
       "      <td>0.887873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>33.0</td>\n",
       "      <td>0.386443</td>\n",
       "      <td>0.891668</td>\n",
       "      <td>0.891743</td>\n",
       "      <td>0.885021</td>\n",
       "      <td>0.885455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>34.0</td>\n",
       "      <td>0.382885</td>\n",
       "      <td>0.893955</td>\n",
       "      <td>0.893942</td>\n",
       "      <td>0.887523</td>\n",
       "      <td>0.888373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>35.0</td>\n",
       "      <td>0.376844</td>\n",
       "      <td>0.891811</td>\n",
       "      <td>0.892263</td>\n",
       "      <td>0.885771</td>\n",
       "      <td>0.886571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>36.0</td>\n",
       "      <td>0.379790</td>\n",
       "      <td>0.893526</td>\n",
       "      <td>0.894903</td>\n",
       "      <td>0.887121</td>\n",
       "      <td>0.888356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>37.0</td>\n",
       "      <td>0.385825</td>\n",
       "      <td>0.889667</td>\n",
       "      <td>0.890507</td>\n",
       "      <td>0.883322</td>\n",
       "      <td>0.884219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>38.0</td>\n",
       "      <td>0.377860</td>\n",
       "      <td>0.896670</td>\n",
       "      <td>0.896575</td>\n",
       "      <td>0.890047</td>\n",
       "      <td>0.890961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>39.0</td>\n",
       "      <td>0.378479</td>\n",
       "      <td>0.893383</td>\n",
       "      <td>0.892662</td>\n",
       "      <td>0.887727</td>\n",
       "      <td>0.887992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>40.0</td>\n",
       "      <td>0.376559</td>\n",
       "      <td>0.893955</td>\n",
       "      <td>0.895700</td>\n",
       "      <td>0.888419</td>\n",
       "      <td>0.889534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>41.0</td>\n",
       "      <td>0.381450</td>\n",
       "      <td>0.893526</td>\n",
       "      <td>0.896254</td>\n",
       "      <td>0.887316</td>\n",
       "      <td>0.888671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>42.0</td>\n",
       "      <td>0.381627</td>\n",
       "      <td>0.892811</td>\n",
       "      <td>0.892399</td>\n",
       "      <td>0.885987</td>\n",
       "      <td>0.886711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>43.0</td>\n",
       "      <td>0.379214</td>\n",
       "      <td>0.892382</td>\n",
       "      <td>0.893415</td>\n",
       "      <td>0.886082</td>\n",
       "      <td>0.887129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>44.0</td>\n",
       "      <td>0.382444</td>\n",
       "      <td>0.892240</td>\n",
       "      <td>0.892632</td>\n",
       "      <td>0.886598</td>\n",
       "      <td>0.887073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>45.0</td>\n",
       "      <td>0.376773</td>\n",
       "      <td>0.894955</td>\n",
       "      <td>0.896270</td>\n",
       "      <td>0.888759</td>\n",
       "      <td>0.889783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>46.0</td>\n",
       "      <td>0.377777</td>\n",
       "      <td>0.892954</td>\n",
       "      <td>0.894033</td>\n",
       "      <td>0.886581</td>\n",
       "      <td>0.887473</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>47.0</td>\n",
       "      <td>0.372839</td>\n",
       "      <td>0.895812</td>\n",
       "      <td>0.895762</td>\n",
       "      <td>0.888733</td>\n",
       "      <td>0.889625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>48.0</td>\n",
       "      <td>0.377827</td>\n",
       "      <td>0.894097</td>\n",
       "      <td>0.896670</td>\n",
       "      <td>0.888401</td>\n",
       "      <td>0.889550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>49.0</td>\n",
       "      <td>0.375955</td>\n",
       "      <td>0.893812</td>\n",
       "      <td>0.895477</td>\n",
       "      <td>0.886459</td>\n",
       "      <td>0.887778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50.0</td>\n",
       "      <td>0.375986</td>\n",
       "      <td>0.893526</td>\n",
       "      <td>0.894978</td>\n",
       "      <td>0.887124</td>\n",
       "      <td>0.888389</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    epoch  test_loss  test_accuracy  test_precision  test_recall  \\\n",
       "0     0.0   4.574569       0.010147        0.007555     0.010026   \n",
       "1     1.0   1.640199       0.587538        0.609600     0.562140   \n",
       "2     2.0   1.113720       0.702730        0.718815     0.679856   \n",
       "3     3.0   0.894771       0.753895        0.749061     0.737337   \n",
       "4     4.0   0.853364       0.757182        0.771304     0.740462   \n",
       "5     5.0   0.735964       0.790196        0.801927     0.778574   \n",
       "6     6.0   0.614825       0.831785        0.830787     0.820846   \n",
       "7     7.0   0.583118       0.837931        0.838710     0.827599   \n",
       "8     8.0   0.584160       0.834929        0.842948     0.824302   \n",
       "9     9.0   0.539541       0.846077        0.850743     0.838852   \n",
       "10   10.0   0.519353       0.853080        0.854708     0.843748   \n",
       "11   11.0   0.467613       0.868801        0.867242     0.860473   \n",
       "12   12.0   0.473727       0.863799        0.867511     0.856654   \n",
       "13   13.0   0.445921       0.875089        0.878064     0.867848   \n",
       "14   14.0   0.442008       0.873374        0.875287     0.865314   \n",
       "15   15.0   0.431930       0.875804        0.877096     0.868570   \n",
       "16   16.0   0.432575       0.878091        0.878309     0.870731   \n",
       "17   17.0   0.414128       0.879377        0.879558     0.871829   \n",
       "18   18.0   0.410965       0.882807        0.883459     0.875738   \n",
       "19   19.0   0.409568       0.883950        0.883950     0.876857   \n",
       "20   20.0   0.403658       0.885665        0.886299     0.879155   \n",
       "21   21.0   0.401694       0.888952        0.887909     0.881970   \n",
       "22   22.0   0.407843       0.885665        0.885989     0.879738   \n",
       "23   23.0   0.406923       0.883807        0.883532     0.876419   \n",
       "24   24.0   0.395577       0.887809        0.889552     0.882043   \n",
       "25   25.0   0.389501       0.889381        0.889916     0.883888   \n",
       "26   26.0   0.387741       0.889667        0.889984     0.883749   \n",
       "27   27.0   0.391301       0.890810        0.891261     0.884622   \n",
       "28   28.0   0.383794       0.890382        0.892840     0.883700   \n",
       "29   29.0   0.383601       0.890810        0.890535     0.884430   \n",
       "30   30.0   0.389712       0.887952        0.887850     0.882333   \n",
       "31   31.0   0.380165       0.891382        0.891478     0.885527   \n",
       "32   32.0   0.382717       0.893383        0.893900     0.887149   \n",
       "33   33.0   0.386443       0.891668        0.891743     0.885021   \n",
       "34   34.0   0.382885       0.893955        0.893942     0.887523   \n",
       "35   35.0   0.376844       0.891811        0.892263     0.885771   \n",
       "36   36.0   0.379790       0.893526        0.894903     0.887121   \n",
       "37   37.0   0.385825       0.889667        0.890507     0.883322   \n",
       "38   38.0   0.377860       0.896670        0.896575     0.890047   \n",
       "39   39.0   0.378479       0.893383        0.892662     0.887727   \n",
       "40   40.0   0.376559       0.893955        0.895700     0.888419   \n",
       "41   41.0   0.381450       0.893526        0.896254     0.887316   \n",
       "42   42.0   0.381627       0.892811        0.892399     0.885987   \n",
       "43   43.0   0.379214       0.892382        0.893415     0.886082   \n",
       "44   44.0   0.382444       0.892240        0.892632     0.886598   \n",
       "45   45.0   0.376773       0.894955        0.896270     0.888759   \n",
       "46   46.0   0.377777       0.892954        0.894033     0.886581   \n",
       "47   47.0   0.372839       0.895812        0.895762     0.888733   \n",
       "48   48.0   0.377827       0.894097        0.896670     0.888401   \n",
       "49   49.0   0.375955       0.893812        0.895477     0.886459   \n",
       "50   50.0   0.375986       0.893526        0.894978     0.887124   \n",
       "\n",
       "    test_f1-score  \n",
       "0        0.005400  \n",
       "1        0.547563  \n",
       "2        0.673580  \n",
       "3        0.731096  \n",
       "4        0.739676  \n",
       "5        0.776723  \n",
       "6        0.818731  \n",
       "7        0.827473  \n",
       "8        0.824956  \n",
       "9        0.839070  \n",
       "10       0.844910  \n",
       "11       0.860667  \n",
       "12       0.857112  \n",
       "13       0.869226  \n",
       "14       0.866243  \n",
       "15       0.868688  \n",
       "16       0.870972  \n",
       "17       0.873091  \n",
       "18       0.876549  \n",
       "19       0.877309  \n",
       "20       0.879998  \n",
       "21       0.882710  \n",
       "22       0.880079  \n",
       "23       0.876910  \n",
       "24       0.882780  \n",
       "25       0.884429  \n",
       "26       0.884701  \n",
       "27       0.885266  \n",
       "28       0.884852  \n",
       "29       0.884803  \n",
       "30       0.882741  \n",
       "31       0.885894  \n",
       "32       0.887873  \n",
       "33       0.885455  \n",
       "34       0.888373  \n",
       "35       0.886571  \n",
       "36       0.888356  \n",
       "37       0.884219  \n",
       "38       0.890961  \n",
       "39       0.887992  \n",
       "40       0.889534  \n",
       "41       0.888671  \n",
       "42       0.886711  \n",
       "43       0.887129  \n",
       "44       0.887073  \n",
       "45       0.889783  \n",
       "46       0.887473  \n",
       "47       0.889625  \n",
       "48       0.889550  \n",
       "49       0.887778  \n",
       "50       0.888389  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "437f128e",
   "metadata": {},
   "source": [
    "# 训练集损失函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eaf1b6e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "x = df_train['batch']\n",
    "y = df_train['train_loss']\n",
    "\n",
    "plt.plot(x, y, label='训练集')\n",
    "\n",
    "plt.tick_params(labelsize=20)\n",
    "plt.xlabel('batch', fontsize=20)\n",
    "plt.ylabel('损失函数', fontsize=20)\n",
    "plt.title('训练集损失函数', fontsize=25)\n",
    "plt.savefig('图表/训练集损失函数.pdf', dpi=120, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58b2fddc",
   "metadata": {},
   "source": [
    "# 训练集准确率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9e285dda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "x = df_train['batch']\n",
    "y = df_train['train_accuracy']\n",
    "\n",
    "plt.plot(x, y, label='训练集')\n",
    "\n",
    "plt.tick_params(labelsize=20)\n",
    "plt.xlabel('batch', fontsize=20)\n",
    "plt.ylabel('准确率', fontsize=20)\n",
    "plt.title('训练集准确率', fontsize=25)\n",
    "plt.savefig('图表/训练集准确率.pdf', dpi=120, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b05aa1bc",
   "metadata": {},
   "source": [
    "# 测试集损失函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d71c5803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "x = df_test['epoch']\n",
    "y = df_test['test_loss']\n",
    "\n",
    "plt.plot(x, y, label='测试集')\n",
    "\n",
    "plt.tick_params(labelsize=20)\n",
    "plt.xlabel('epoch', fontsize=20)\n",
    "plt.ylabel('损失函数', fontsize=20)\n",
    "plt.title('测试集损失函数', fontsize=25)\n",
    "plt.savefig('图表/测试集损失函数.pdf', dpi=120, bbox_inches='tight')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c75f633",
   "metadata": {},
   "source": [
    "# 测试集评估指标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "49c7eb79",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import colors as mcolors\n",
    "import random\n",
    "random.seed(124)\n",
    "colors = ['b', 'g', 'r', 'c', 'm', 'y', 'k', 'tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan', 'black', 'indianred', 'brown', 'firebrick', 'maroon', 'darkred', 'red', 'sienna', 'chocolate', 'yellow', 'olivedrab', 'yellowgreen', 'darkolivegreen', 'forestgreen', 'limegreen', 'darkgreen', 'green', 'lime', 'seagreen', 'mediumseagreen', 'darkslategray', 'darkslategrey', 'teal', 'darkcyan', 'dodgerblue', 'navy', 'darkblue', 'mediumblue', 'blue', 'slateblue', 'darkslateblue', 'mediumslateblue', 'mediumpurple', 'rebeccapurple', 'blueviolet', 'indigo', 'darkorchid', 'darkviolet', 'mediumorchid', 'purple', 'darkmagenta', 'fuchsia', 'magenta', 'orchid', 'mediumvioletred', 'deeppink', 'hotpink']\n",
    "markers = [\".\",\",\",\"o\",\"v\",\"^\",\"<\",\">\",\"1\",\"2\",\"3\",\"4\",\"8\",\"s\",\"p\",\"P\",\"*\",\"h\",\"H\",\"+\",\"x\",\"X\",\"D\",\"d\",\"|\",\"_\",0,1,2,3,4,5,6,7,8,9,10,11]\n",
    "linestyle = ['--', '-.', '-']\n",
    "def get_line_arg():\n",
    "    '''\n",
    "    随机产生一种绘图线型\n",
    "    '''\n",
    "    line_arg = {}\n",
    "    line_arg['color'] = random.choice(colors)\n",
    "    # line_arg['marker'] = random.choice(markers)\n",
    "    line_arg['linestyle'] = random.choice(linestyle)\n",
    "    line_arg['linewidth'] = random.randint(1, 4)\n",
    "    # line_arg['markersize'] = random.randint(3, 5)\n",
    "    return line_arg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9f9e339f",
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics = ['test_accuracy', 'test_precision', 'test_recall', 'test_f1-score']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "36d7c34c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16, 8))\n",
    "\n",
    "x = df_test['epoch']\n",
    "for y in metrics:\n",
    "    plt.plot(x, df_test[y], label=y, **get_line_arg())\n",
    "\n",
    "plt.tick_params(labelsize=20)\n",
    "plt.ylim([0, 1])\n",
    "plt.xlabel('epoch', fontsize=20)\n",
    "plt.ylabel('评估指标', fontsize=20)\n",
    "plt.title('测试集分类评估指标', fontsize=25)\n",
    "plt.savefig('图表/测试集分类评估指标.pdf', dpi=120, bbox_inches='tight')\n",
    "\n",
    "plt.legend(fontsize=20)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
